Molecular Mechanisms Underlying Anticancer and Anti-Inflammatory Activities of Oridonin in Oral Squamous Cell Carcinoma
Why this work is in the frame
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Bibliographic record
Abstract
Background. Oral squamous cell carcinoma (OSCC) constitutes one of the most common pathological forms of oral cancers. Oridonin is an ent-kaurane diterpenoid compound isolated from Rabdosia rubescens. Recently, the anticancer potential of Oridonin has been extensively studied in breast, osteosarcoma, myeloma, neuroblastoma, lymphoma, pancreatic, colon, leukemia, and esophageal cancers. The anticancer potential of Oridonin is largely unexplored in OSCC. Method. This study aimed to provide insights into the multifunctional anticancer activities of Oridonin in OSCC. We carried out an extensive and critical literature survey on research related to the importance of medicinal plants in various cancers, role of Oridonin as potential anticancer agents in OSCC up to 2025 using keywords apoptotic proteins, antitumor activities, cell cycle arrest, diterpenoid, inflammasomes, Notch signaling pathway, natural products, Oridonin, oral squamous cell carcinoma, and oral cancer treatment. Results. Oridonin induces cell apoptosis in oral cancer cells (OCC) by regulating mitochondrial and ROS-mediated JNK/p38 MAPK, acting as cell cycle blocker at the G2/M phase pathways, and increasing the expression of γH2AX. Oridonin plays an essential role in OSCC tumorigenesis by inhibiting the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway. Blocking Notch signaling dysregulation and specific inhibition of NLRP3 inflammasome are the other cellular mechanism by which Oridonin can exhibit its antitumor activities. Conclusion. Oridonin can serve as a potential anticancer drug in OSCC due to its involvement in multiple cellular signaling pathways.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it